In order to build up a bridge between quality and productivity, the present study highlights optimization of turning process parameters to provide good surface finish as well as high hardness. The objective of this paper is to solve the multi- response parameter optimization problems of turning process. By applying Taguchi method the quality of manufactured goods, and engineering designs are developed by studying variations. In this work, an attempt has been made to solve the correlated multiple criteria optimization problem of turning process by considering the major performance characteristics hardness and surface roughness. The corresponding machining parameters are cutting-speed, feed and depth of cut. Traditional Taguchi based hybrid optimization approaches rely on the assumption that quality indices are uncorrelated or independent. But it is felt that, in practice, there may be some correlation among various quality indices (responses) under consideration. To overcome this limitation of Taguchi approach, the present study proposes application of PCA to convert correlated responses into uncorrelated quality indices called individual principal components. The Composite Principle Component has been optimized by using Taguchi method. Analysis of variance (ANOVA) has been conducted for Composite Principle Component to find the optimal process parameters. Signal to Noise (S/N) Ratio has been found for PCA to find the optimal levels of the process parameters. Finally a conformation test has been made for three different materials and the results have been plotted.